Responsibilities
- Lead and mentor a team of statistical programmers, fostering development and high performance.
- Oversee internal and vendor/CRO programming deliverables, ensuring timelines and quality expectations are met.
- Establish and maintain programming standards, documentation, and best practices.
- Support planning, resourcing, and prioritization for programming activities across multiple studies.
- Oversee development and validation of SDTM and ADaM datasets according to CDISC standards and oncology study requirements.
- Supervise creation of Tables, Listings, and Figures (TLFs) for clinical study reporting and regulatory submissions.
- Ensure all deliverables are of high quality, reproducible, and aligned with regulatory expectations (e.g., FDA, EMA).
- Support automation and efficiency initiatives using SAS and/or R.
- Perform and review QC checks, resolving programming and data issues.
- Partner closely with Biostatistics, Clinical Data Management, Medical Writing, and Regulatory teams.
- Participate in study team meetings, contributing programming perspective to clinical and data discussions.
- Support preparation of submission-ready deliverables, including reviewer guides, traceability documents, and regulatory artifacts.
Requirements
- Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, Life Sciences, or related field.
- 9–11+ years of statistical programming experience in the pharmaceutical/biotech/CRO environment.
- Strong proficiency in SAS programming
- Expert understanding of CDISC standards (SDTM, ADaM).
- Experience managing or mentoring programming teams.
- Demonstrated experience supporting regulatory submissions.
- Excellent communication skills and ability to work collaboratively across functions.
Nice to Have
- Experience with R
Work Arrangement
Hybrid
Additional Information
- language requirements: null
- travel: null
- hours: null
- shifts: null
- equipment: null
- clearance: null
- background checks: null
- contract duration: null
- probation: null
- relocation: null
- training: null
